Optimizing drug combinations to resurrect the potency of failed antibody therapy against emerging COVID-19 variants using IDentif.AI - Summary - MDSpire

Optimizing drug combinations to resurrect the potency of failed antibody therapy against emerging COVID-19 variants using IDentif.AI

  • By

  • Peter Wang

  • Kui You

  • Zi Wei Chia

  • Lissa Hooi

  • Li Ming Chong

  • De Hoe Chye

  • Angelina Moh

  • Ze Yong Lee

  • Ethan Lim

  • Alrick Zi Xin Kok

  • Stephen Chua

  • Isaiah Zhuang

  • Ella Chang

  • Boon Huan Tan

  • Gladys Gek Yen Tan

  • Shawn Vasoo

  • Conrad E. Z. Chan

  • Edward Kai-Hua Chow

  • Dean Ho

  • June 2, 2026

  • 0 min

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Objective:

To optimize and prioritize drug combinations that enhance the potency of sotrovimab (STV) against the SARS-CoV-2 Omicron XBB subvariant, in light of its reduced efficacy.

Key Findings:
  • IDentif.AI identified STV/EIDD-1931 and STV/GS-441524 combinations that synergistically enhanced efficacy against XBB, reducing STV's in vitro EC50 by up to 7-fold.
Interpretation:

Limitations:
  • The study primarily focuses on in vitro results, which may not fully translate to in vivo efficacy.
  • The effectiveness of the identified combinations in clinical settings remains to be validated.
Conclusion:

The study demonstrates the use of IDentif.AI to identify drug combinations that may enhance the efficacy of previously authorized drugs against emerging variants.

Original Source(s)

Optimizing drug combinations to resurrect the potency of failed antibody therapy against emerging COVID-19 variants using IDentif.AI

  • by Peter Wang, Kui You, Zi Wei Chia, Lissa Hooi, Li Ming Chong, De Hoe Chye, Angelina Moh, Ze Yong Lee, Ethan Lim, Alrick Zi Xin Kok, Stephen Chua, Isaiah Zhuang, Ella Chang, Boon Huan Tan, Gladys Gek Yen Tan, Shawn Vasoo, Conrad E. Z. Chan, Edward Kai-Hua Chow, Dean Ho

  • June 2, 2026

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